Leveraging Intelligent Building Infrastructure for Event Response

The number of attacks against occupied commercial buildings has increased dramatically around the world and in the United States. These attacks have included active shooters, kinetic devices, and hazardous (i.e., chemical or biological) agents. Typical commercial buildings have no systems to deal with these threats. Even iconic buildings rely primarily on restricted access to provide security. Video cameras are often present but are used primarily for forensics after an event has occurred. However, advanced systems that enable intelligent and connected buildings can be leveraged along with sensor technology to enable detection, notification and response to attacks. These same systems can also be used to enhance response to other emergency events such as grid outages, extreme weather, and earthquakes. This paper will present current research showing how Intelligent Building Technology can be leveraged to provide automated response and situational awareness to attacks and other emergency event situations. Results from whole-building modeling and full-scale testing will be presented for one type of threat. Specifically, CONTAM model results validated with experimental data from a well-instrumented 50,000 sqft testbed building will be presented to demonstrate the capability of using intelligent building infrastructure to affect dispersion of a chemical or biological agent inside a commercial office building

Evaluation of Optimal Chiller Plant Control Algorithms in Model-Based Design Platform with Hardware-in-the-Loop

Chiller systems account for 31% of the total cooling electricity consumption of medium-sized commercial buildings within 25k-200k square feet. In the last decade, advanced controls such as model predictive control (MPC) has demonstrated energy savings that typically range from 5% to 15%. However, the installation and commissioning efforts to deploy MPC into existing building automation system (BAS) are often cost prohibitive and therefore undermine the energy saving benefit it brings into the game. This paper presents a framework and results of using model-based design (MBD) to evaluate the benefit and trade-offs of different chiller plant control algorithms for medium-sized commercial buildings including an optimization-based algorithm that can be deployed rapidly with little installation and commission effort. A high-fidelity dynamic simulation model for selected building types and climate zones were developed and implemented in the hardware-in-the-loop (HiL) platform. Baseline and optimization-based control algorithms were deployed in Automated Logic Corporation (ALC) controller hardware with their performance monitored through WebCtrl in real-time. The first contribution of this paper is the development and successful integration of Modelica-based high-fidelity dynamic models of chiller plants, air-handling units, and building envelope and zones. The building types of medium office and large hotel were selected and modeled in details. In particular, the building envelope and zone models were developed based on a direct translation of the selected DOE EnergyPlus reference building models, which are widely accepted in the building modeling community. The chiller plant was modeled with physics-based components such as chillers, pumps, valves, and pipes that include typical dynamics in a real chiller plant. Both primary-secondary and primary-only configurations were modeled and considered in the controls evaluation. The air handling unit was modeled based on the component models from Modelica Buildings Library developed by LBNL and includes a finite-volume based cooling coil model capable of calculating latent heat transfer. The second contribution of this paper is the demonstration of utilizing HiL platform to benchmark baseline and optimal control algorithms based on detailed whole-building level dynamic models. In the HiL setup, a real-world hardware controller is coupled to the high-fidelity simulation model and operates in real-time. The HiL setup provides the same interface for installation of overlay software as it would be a demonstration site BAS, eliminates the risk associated with seasonal operation and availability in demonstration sites, enables precise evaluation of energy savings potential for various internal and external building load scenarios

Assisted Point Mapping to Enable Cost-effective Deployment of Intelligent Building Applications

Over the past years intelligent building applications that promise to dramatically reduce energy consumption, improve occupant comfort and streamline maintenance have been proposed. However their adoption has met a step barrier in the unexpectedly high cost in mapping data from building automation systems into these applications’ data models. In fact the industry does not have a common convention on how to name points. Generally, names are correlated with the semantic of the variables they represent, but typically engineers have the freedom to set up variable names according to their preferences. In order to meet market requirements, an “ideal†algorithm would have four properties: 1) high accuracy and especially low false positive rate (i.e. small number of erroneously mapped points); 2) ability to infer complex relationships between data points (e.g. grouping points by equipment, classifying equipment, establishing relationship between equipment); 3) easy to use: it should leverage only readily available knowledge and data about the system (i.e. not requiring the installation of additional sensors); 4) minimizing the need of having a domain expert using it. In the last few years the research community has devoted increasing attention in automating the process of mapping data points from existing BAS. However, none of the published work meets the market requirements. Most require an expert user, some are not “easy to use†and none can automatically infer complex relationships. This paper presents a novel algorithm and its software implementation to tackle the mapping problem. This work contributes moving the state-of-the-art a bit further in the sense that this algorithm can be applied to various dataset with minor or no modification (i.e. no expert in the loop), it is the first to automatically infer complex relationships and it only ingests point names as input (i.e. easiness of use). The algorithm has been tested against the largest and most diversified dataset in the literature comprising 25299 points, 7 buildings, 4 vendors and 3 distributors. Preliminary results suggest that it is able to correctly map about 92% of the point required by a test application and to successfully identify about 92% of VAVs, 100% of AHU and FCU

Lab and Field Evaluation of Fault Detection and Diagnostics for Advanced Roof Top Unit

In this paper, the results of lab and field evaluation of several RTU FDD technologies will be presented and discussed. The focus the study was on RTUs that provide cooling of small and medium commercial buildings. This work was conducted by UTRC in close collaboration Purdue University within Consortium for Building Energy Innovation (CBEI). The goal of the lab activity was to engineer and assess low-cost, embeddable fault detection and diagnostics (FDD) for a new RTU product that exceeds DOE\u27s High Performance RTU performance specification. Primary focus of evaluation was on overall unit performance degradation (COP and capacity) resulted from single and multiple operational faults. High confidence and low false alarm rate of COP degradation were demonstrated. The cost effectiveness of FDD will be discussed. Due to high interest and close engagement of Original Equipment Manufacturer (OEM) and National Account Customer field evaluation of FDD became possible. Several commercial sited with state-of-the-art RTUs were instrumented for continues monitoring of RTU performance and assessment of frequency of typical operational faults. Also some operational faults are intentionally injected in order evaluate FDD effectiveness. Several levels of FDD applicable in the field will be discussed

Analysis of Automated Fault Detection and Diagnostics Records as an Indicator of HVAC Fault Prevalence: Methodology and Preliminary Results

Faults in commercial buildings can cause energy waste and other performance problems such as reduced occupant comfort, reduced equipment longevity, and increased noise. However, it is currently unknown how commonly faults occur in different equipment types. This paper describes a method to estimate the prevalence of faults in air handling units, air terminal units, and rooftop units and the use of three metrics for summarizing results. This method was developed by the authors as part of a study which includes data from several automated fault detection and diagnostics (AFDD) data providers, providing a large sample with a wide range of building types, geographical locations, and equipment types. This dataset includes fault diagnoses from thousands of buildings throughout the United States, as well as anonymized metadata describing the building and equipment characteristics. The number of fault records is on the order of 106. We describe here how the data from different data providers can be processed and unified using a common taxonomy, and illustrate three metrics that can provide insights using this type of data. The methods developed for this study are illustrated here with preliminary data. This work supports a multi-year, multi-institutional project that will provide insight into the drivers of fault prevalence; for example, whether prevalence is correlated with characteristics like building type, building size, and geographical location (including related factors like local climate and utility rates). We discuss some of the challenges of harmonizing disparate outputs from multiple AFDD providers, the usefulness of applying a unifying fault taxonomy, and provide preliminary figures that illustrate three fault prevalence metrics

Identification of the Biotransformation Products of 2-Ethylhexyl 4-(N,N-Dimethylamino)benzoate

Nowadays, 2-ethylhexyl 4-(N,N-dimethylamino)benzoate (EDP) is one of the most widely used UV filters in sunscreen cosmetics and other cosmetic products. However, undesirable processes such as percutaneous absorption and biological activity have been attributed to this compound. The in vitro metabolism of EDP was elucidated in the present work. First of all, the phase I biotransformation was studied in rat liver microsomes and two metabolites, N,N-dimethyl-p-aminobenzoic acid (DMP) and N-monomethyl-p-aminobenzoic acid (MMP), were identified by GC-MS analysis. Secondly, the phase II metabolism was investigated by means of LC-MS. The investigated reactions were acetylation and glucuronidation working with rat liver cytosol and with both human and rat liver microsomes, respectively. Analogue studies with p-aminobenzoic acid (PABA) were carried out in order to compare the well established metabolic pathway of PABA with the unknown biotransformation of EDP. In addition, a method for the determination of EDP and its two phase I metabolites in human urine was developed. The methodology requires a solid-phase extraction prior to LC-MS analysis. The method is based on standard addition quantification and has been fully validated. The repeatability of the method, expressed as relative standard deviation, was in the range 3.4–7.4% and the limit of detection for all quantified analytes was in the low ng mL−1 range

Carbon-sensitive pedotransfer functions for plant available water

Currently accepted pedotransfer functions show negligible effect of management-induced changes to soil organic carbon (SOC) on plant available water holding capacity (θAWHC), while some studies show the ability to substantially increase θAWHC through management. The Soil Health Institute\u27s North America Project to Evaluate Soil Health Measurements measured water content at field capacity using intact soil cores across 124 long-term research sites that contained increases in SOC as a result of management treatments such as reduced tillage and cover cropping. Pedotransfer functions were created for volumetric water content at field capacity (θFC) and permanent wilting point (θPWP). New pedotransfer functions had predictions of θAWHC that were similarly accurate compared with Saxton and Rawls when tested on samples from the National Soil Characterization database. Further, the new pedotransfer functions showed substantial effects of soil calcareousness and SOC on θAWHC. For an increase in SOC of 10 g kg–1 (1%) in noncalcareous soils, an average increase in θAWHC of 3.0 mm 100 mm–1 soil (0.03 m3 m–3) on average across all soil texture classes was found. This SOC related increase in θAWHC is about double previous estimates. Calcareous soils had an increase in θAWHC of 1.2 mm 100 mm–1 soil associated with a 10 g kg–1 increase in SOC, across all soil texture classes. New equations can aid in quantifying benefits of soil management practices that increase SOC and can be used to model the effect of changes in management on drought resilience

Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity

Pressure UlceR Programme Of reSEarch (PURPOSE): using mixed methods (systematic reviews, prospective cohort, case study, consensus and psychometrics) to identify patient and organisational risk, develop a risk assessment tool and patient-reported outcome Quality of Life and Health Utility measures

Background: The Pressure UlceR Programme Of reSEarch (PURPOSE) consisted of two themes. Theme 1 focused on improving our understanding of individuals’ and organisational risk factors and on improving the quality of risk assessments (work packages 1–3) and theme 2 focused on developing patient-reported outcome measures (work packages 4 and 5). Methods: The programme comprised 21 individual pieces of work. Pain: (1) multicentre pain prevalence study in acute hospitals, (2) multicentre pain prevalence study in community localities incorporating (3) a comparison of case-finding methods, and (4) multicentre, prospective cohort study. Severe pressure ulcers: (5) retrospective case study, (6) patient involvement workshop with the Pressure Ulcer Research Service User Network for the UK (PURSUN UK) and (7) development of root cause analysis methodology. Risk assessment: (8) systematic review, (9) consensus study, (10) conceptual framework development and theoretical causal pathway, (11) design and pretesting of draft Risk Assessment Framework and (12) field test to assess reliability, validity, data completeness and clinical usability. Quality of life: (13) conceptual framework development (systematic review, patient interviews), (14 and 15) provisional instrument development, with items generated from patient interviews [from (1) above] two systematic reviews and experts, (16) pretesting of the provisional Pressure Ulcer Quality of Life (PU-QOL) instrument using mixed methods, (17) field test 1 including (18) optimal mode of administration substudy and item reduction with testing of scale formation, acceptability, scaling assumptions, reliability and validity, and (19) field test 2 – final psychometric evaluation to test scale targeting, item response categories, item fit, response bias, acceptability, scaling assumptions, reliability and validity. Cost–utility: (20) time trade-off task valuations of health states derived from selected PU-QOL items, and (21) validation of the items selected and psychometric properties of the new Pressure Ulcer Quality of Life Utility Index (PUQOL-UI). Key findings:Pain: prevalence studies – hospital and community patients experience both pressure area-related and pressure ulcer pain; pain cohort study – indicates that pain is independently predictive of category 2 (and above) pressure ulcer development. Severe pressure ulcers: these were more likely to develop in contexts in which clinicians failed to listen to patients/carers or recognise/respond to high risk or the presence of an existing pressure ulcer and services were not effectively co-ordinated; service users found the interactive workshop format valuable; including novel components (interviews with patients and carers) in root cause analysis improves the quality of the insights captured. Risk assessment: we developed a Pressure Ulcer Risk Assessment Framework, the PURPOSE-T, incorporating the Minimum Data Set, a screening stage, a full assessment stage, use of colour to support decision-making, and decision pathways that make a clear distinction between patients with an existing pressure ulcer(s) (or scarring from previous ulcers) who require secondary prevention and treatment and those at risk who require primary prevention (http://medhealth.leeds.ac.uk/accesspurposet). Quality of life: the final PU-QOL instrument consists of 10 scales to measure pain, exudate, odour, sleep, vitality, mobility/movement, daily activities, emotional well-being, self-consciousness and appearance, and participation (http://medhealth.leeds.ac.uk/puqol-ques). Cost–utility: seven items were selected from the PU-QOL instrument for inclusion in the PUQOL-UI (http://medhealth.leeds.ac.uk/puqol-ui); secondary study analysis indicated that item selection for the PUQOL-UI was appropriate and that the index was acceptable to patients and had adequate levels of validity. Conclusions: The PURPOSE programme has provided important insights for pressure ulcer prevention and treatment and involvement of service users in research and development, with implications for patient and public involvement, clinical practice, quality/safety/health service management and research including replication of the pain risk factor study, work exploring ‘best practice’ settings, the impact of including skin status as an indicator for escalation of preventative interventions, further psychometric evaluation of PU-QOL and PUQOL-UI the measurement of ‘disease attribution.’ Funding: The National Institute for Health Research Programme Grants for Applied Research programme